The Drought Calculator: Decision Support Tool for Predicting Forage Growth During Drought

The Drought Calculator (DC), a spreadsheet-based decision support tool, was developed to help ranchers and range managers predict reductions in forage production due to drought. Forage growth potential (FGP), the fraction of historical average production, is predicted as a weighted average of monthly precipitation from January through June. We calibrated and evaluated the DC tool in the Great Plains of the United States, using FGP and precipitation data from Colorado (CO), North Dakota (ND), and Wyoming (WY). In CO, FGP was most sensitive to precipitation in April and May, in ND to precipitation in April and June, and in WY to precipitation in April, May, and June. Weights in these months ranged from 0.16 to 0.52. Prediction was better for CO and WY than for ND. When January–June precipitation was used, the tool correctly predicted 83% of the years with FGP reduced by drought for CO, 82% for WY, and only 67% for ND. Positive values of the True Skill Statistic (0.53 for CO, 0.42 for WY, and 0.17 for ND) indicate that FGP was classified as above or below average better than random selection. Predicting FGP earlier than April in CO and WY will require accurate forecasts of April–June precipitation. Use of the DC is most limited by insufficient forage data to determine the site-specific relationships between FGP and monthly precipitation. Even so, the decision tool is useful for discriminating drought effects on FGP classification being above or below the long-term average, and it provides a quantitative prediction to producers for their destocking decisions in drought years.     

Nitrogen Fertilizer Management Practices to Reduce N<Subscript>2</Subscript>O Emissions from Irrigated Processing Potato in Manitoba

Nitrogen fertilizer practices affect nitrous oxide (N₂O) emissions from agricultural soils. The “4R” nutrient stewardship framework of using N fertilizer at the right rate, right source, right placement and right time can reduce N₂O emissions while maintaining or improving yield of field crops, but understanding of how the various factors affect N₂O emissions from irrigated processing potato is lacking. We examined the effects of selected 4R practices on emissions, using results from two irrigated processing potato studies each conducted in 2011 and 2012 in Manitoba, Canada. Experiment 1 examined combinations of source (urea, ESN), placement (pre-plant incorporation [PPI], banding), and rate (100 and 200 kg N ha^-1) on a clay loam soil. Experiment 2 examined timing and source treatment combinations (urea PPI, ESN PPI, urea split, urea split/fertigation) on a loamy fine sandy soil. For Experiment 1, use of ESN at 200 kg ha^-1 did not reduce area-, yield- and applied fertilizer N- based N₂O emissions compared to urea at 200 kg ha^-1, irrespective of placement. Emissions from pre-plant banding ESN at 200 kg ha^?1, however, were 32% lower than from PPI ESN. For Experiment 2, compared to single pre-plant urea application, fertigation simulated by in-season application of urea ammonium nitrate (UAN) gave lower area-, yield- and applied fertilizer N- based emissions. Split urea ( \( \raisebox{1ex}{$2$}\!\left/ \!\raisebox{-1ex}{$3$}\right. \) pre-plant, \( \raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$3$}\right. \) hilling) also reduced area- and yield- based N₂O emissions compared to single pre-plant urea application. Emissions were generally lower at the site with loamy fine sandy soil than the site with clay loam soil. These results demonstrate that combinations of “4R” practices rather than source alone are best to achieve reductions in N₂O emissions from irrigated potato production.     

Determining corn nitrogen rates using multiple prediction models

Weather uncertainty and soil spatial variability impact nitrogen (N) cycling and corn (Zea mays L.) growth, making accurate N predictions a challenge. Field studies were conducted in Lansing, Michigan, to evaluate a computer model (i.e., Adapt-N), a preseason year-based model (i.e., maximum return to N [MRTN]), and a crop sensor model (i.e., active canopy sensor with algorithm) for recommending corn N rates. To determine site-specific economic optimum N rates (EONR), five N rates were also applied (0, 33%, 66%, 133%, and 166% of the suggested MRTN) as starter + sidedress (SD) at V4. In a wet year (i.e., 2015), Adapt-N increased V8 SD N rates 35 kg N ha^?1 relative to the MRTN V4 SD N application. Although the greater rate of N may have provided additional yield protection, no statistical yield differences were observed between the two models. The MRTN model increased partial factor productivity (PFP) 20% relative to Adapt-N. Limited expression of V8 corn N deficiency reduced crop sensor total N rates (21–56 kg N ha^?1) and yield (0.82–1.05 Mg ha^?1) relative to other models. In a drier year (i.e., 2016), N demand was reduced (EONR 64 kg N ha^?1 less than 2015), resulting in similar corn response to all three models. Despite differences in actual corn N rate recommendations, all three models resulted in similar economic net returns across study years.

Abbreviations: EONR, economic optimum nitrogen rate; MRTN, Maximum Return to Nitrogen; NUE, nitrogen-use efficiency; PFP, partial factor productivity; SBNRC, sensor-based nitrogen rate calculator; SD, side-dress     

First evidence of spawning migration by goldfish (Carassius auratus); implications for control of a globally invasive species

Goldfish (Carassius auratus) was one of the first fishes to be domesticated and has been widely introduced across the globe, but is now considered one of the world's worst invasive aquatic species. Surprisingly, there is a dearth of information on its spatial and temporal movement patterns, which hampers the development of effective control programmes. We examined the movement patterns of an introduced population of C. auratus in a south‐western Australian river using passive acoustic telemetry. The study population had a high residency index within the array (i.e. proportion of all days at liberty that, on average, each fish was detected by a receiver) with fish being detected on 64% of days. The individuals were also reasonably mobile, travelling a mean of 0.30 km (linear river kilometres).day^‐1 within the array, and one fish moved 231.3 km over the 365‐day study period (including 5.4 km in a 24 hr period). Importantly, C. auratus displayed significant seasonal movement patterns including a clear shift in habitats during its breeding period with most mature individuals being detected in an off‐channel wetland during that time. The results of this study strongly suggest that C. auratus undertook a spawning migration into a lentic habitat. These results have important implications for developing control programmes for the species, such as targeting connections to off‐channel lentic systems during its breeding period.     

Distribution of Salmonella serovars and phage types on 80 Ontario swine farms in 2004

The objective of this study was to describe the distribution of Salmonella spp. on Ontario grower-finisher pig farms. Eighty swine farms were visited from January through July 2004. On each farm, fecal samples were collected from 5 pens, 2 rectal samples and 1 pooled sample from fresh manure on the floor per pen. Salmonella was isolated from 91 (11%) of the 800 rectal samples and 73 (18%) of the 397 pooled samples. Overall, Salmonella was recovered from 37 (46%) of the 80 farms. On each positive farm, Salmonella was cultured from 1 to 7 pigs or 1 to 5 pens. Of the 37 farms, 18, 13, 5, and 1 yielded 1, 2, 3, and 4 serovars, respectively. The most common serovars were S. Typhimurium var. Copenhagen, S. Infantis, S. Typhimurium, S. Derby, S. Agona, S. Havana, and S. enterica subsp. I:Rough-O. The 3 most frequent phage types were PT 104, PT 104a, and PT 104b. There was a statistically fair agreement between samples collected directly from pigs and pooled pen samples in determining the Salmonella status at the pen and farm level (kappa = 0.6, P < 0.0001). However, in 62 pens, Salmonella status, serovars, or phage types differed between the pig and pooled pen samples. The distribution of Salmonella on the swine farms in this study indicates that, in developing an intervention strategy, priority should be given to farms positive for S. Typhimurium var. Copenhagen. Also, the variation in Salmonella status between pig and pooled pen samples deserves consideration in a sampling strategy.     

Relationships between demographic variables and lead toxicosis in cattle evaluated at North American veterinary teaching hospitals

OBJECTIVE: To determine associations between age, sex, breed, and month and year of admission and the diagnosis of lead toxicosis in cattle. DESIGN: Retrospective case-control study. Sample Population-Records of all cattle evaluated at North American veterinary teaching hospitals during the years 1963 to 2002, which were available through the Veterinary Medical Database. PROCEDURES: Logistic regression was used to evaluate the associations between postulated risk factors and the occurrence of lead toxicosis in cattle and predict the occurrence of the diagnosis of lead toxicosis in cattle. RESULTS: 413 cases of lead intoxication and 202,363 control cattle were identified and met the inclusion criteria. Cattle < 4 years of age were at increased risk for the diagnosis of lead intoxication relative to cattle > or = 4 years of age. Cattle > or = 2 months and < 6 months of age had the greatest risk for lead intoxication (odds ratio, 12.3). Angus cattle were at greater risk for toxicosis (odds ratio, 1.95), compared with other breeds. The risk of lead toxicosis was greater before 1985 (odds ratio, 1.94) than the risk thereafter. The risk of lead toxicosis diagnosis was greatest in the months of May, June, July, and August. CONCLUSIONS AND CLINICAL RELEVANCE: Lead toxicosis in cattle was associated with age < 4 years and the Angus breed. A seasonal pattern existed with peak occurrence in the late spring and summer. The occurrence of lead toxicosis has declined over time.     

Surgical approaches for cesarean section in cattle

Bovine practitioners are often presented with dystocias that require a cesarean section. Many practitioners perform this surgery using the same approach each time due to their comfort with one specific approach or lack of familiarity of other available options. The goal of this article is to explain the advantages, disadvantages, and indications for each of the different approaches to aid the practitioner in achieving better surgical success rate.